Symbiont Diversity Ecology Data
Shakeal Hodge
8/10/2021
library(ggplot2)
library(RColorBrewer)
library(readr)
library(stringr)
library(forcats)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union#Load the Data
Can be used to load files created from SymVals/HostVals data
fullcubeHelix <- c("#673F03", "#7D3002", "#891901", "#A7000F", "#B50142", "#CD0778", "#D506AD", "#E401E7", "#AB08FF","#7B1DFF", "#5731FD","#5E8EFF", "#4755FF" ,"#6FC4FE", "#86E9FE", "#96FFF7", "#B2FCE3", "#BBFFDB", "#D4FFDD", "#EFFDF0")
shorthelix <- c("#A7000F", "#E401E7","#5E8EFF","#86E9FE","#B2FCE3")
elevenhelix <- c("#673F03", "#891901", "#B50142", "#D506AD", "#AB08FF", "#5731FD", "#4755FF", "#86E9FE", "#B2FCE3", "#D4FFDD", "#EFFDF0")
tenhelix <- c("#891901", "#B50142", "#D506AD", "#AB08FF","#000000","#4755FF" , "#86E9FE", "#B2FCE3", "#D4FFDD", "#EFFDF0")setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-10-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#20 Symbionts per Host
##Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-20-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.##Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#40 Symbionts per Host
#Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-40-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#50 Symbionts per Host
Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-50-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#60 Symbionts per Host
##Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-60-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#!00 Symbionts per Host
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-100-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#1000 Symbionts per Host
##Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
## Plots
all_data <- read_table2("munged_area_mult-sym-1000-s.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0.0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Create SymVals Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#SymDiveristy Data for 10 Symbionts per Host
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
all_data <- read_table2("munged_symDiv_area_mult-sym-10.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "0_1" ~ "0 to 1 ",
interval == "1_2" ~ "1 to 2 ",
interval == "2_3" ~ "2 to 3 ",
interval == "3_4" ~ "3 to 4 ",
interval == "4_5" ~ "4 to 5 ",
interval == "5_6" ~ "5 to 6 ",
interval == "6_7" ~ "6 to 7 ",
interval == "7_8" ~ "7 to 8 ",
interval == "8_9" ~ "8 to 9 ",
interval == "9_10" ~ "9 to 10 ",
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
# Reorder interaction rate factor to be in correct numeric order:
# - First, we turn interval into a numeric variable that just holds the first number of each bin
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.#Host Variance Data plots
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
#Host Mean Data plots
##Load the Data
setwd("C:/Users/shake/OneDrive/Documents/GitHub/SymbulationEmp/stats_scripts")
all_data <- read_table2("munged_symDivMean_area_mult-sym-10.dat") # Load data##
## -- Column specification --------------------------------------------------------
## cols(
## treatment = col_double(),
## seed = col_double(),
## update = col_character(),
## interval = col_character(),
## count = col_character(),
## partner = col_character()
## )all_data <- all_data %>% filter(update != "update") # remove extra header rows
all_data$update <- as.numeric(all_data$update) # Treat update as numeric
all_data$count <- as.numeric(all_data$count) # Treat count as numeric
all_data <- all_data %>% mutate( # Create column for heat map label
Interaction_Rate = case_when(
interval == "-1_-.9" ~ "-1 to -0.8 (Parasitic)",
interval == "-.9_-.8" ~ "-1 to -0.8 (Parasitic)",
interval == "-.8_-.7" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.7_-.6" ~ "-0.8 to -0.6 (Parasitic)",
interval == "-.6_-.5" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.5_-.4" ~ "-0.6 to -0.4 (Detrimental)",
interval == "-.4_-.3" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.3_-.2" ~ "-0.4 to -0.2 (Detrimental)",
interval == "-.2_-.1" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "-.1_0" ~ "-0.2 to 0 (Nearly Neutral)",
interval == "0_.1" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".1_.2" ~ "0 to 0.2 (Nearly Neutral)",
interval == ".2_.3" ~ "0.2 to 0.4 (Positive)",
interval == ".3_.4" ~ "0.2 to 0.4 (Positive)",
interval == ".4_.5" ~ "0.4 to 0.6 (Positive)",
interval == ".5_.6" ~ "0.4 to 0.6 (Positive)",
interval == ".6_.7" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".7_.8" ~ "0.6 to 0.8 (Mutualistic)",
interval == ".8_.9" ~ "0.8 to 1.0 (Mutualistic)",
interval == ".9_1" ~ "0.8 to 1.0 (Mutualistic)"
),
Rate = case_when( # Create column for vertical transmission rate label
treatment == 0 ~ "0%",
treatment == 0.05 ~ "5%",
treatment == 0.06 ~ "6%",
treatment == 0.07 ~ "7%",
treatment == 0.08 ~ "8%",
treatment == 0.09 ~ "9%",
treatment == 0.1 ~ "10%",
treatment == 0.2 ~ "20%",
treatment == 0.3 ~ "30%",
treatment == 0.4 ~ "40%",
treatment == 0.5 ~ "50%",
treatment == 0.6 ~ "60%",
treatment == 0.7 ~ "70%",
treatment == 0.8 ~ "80%",
treatment == 0.9 ~ "90%",
treatment == 1 ~ "100%",
)
)
all_data$interval <- as.numeric(str_extract(all_data$interval, "^-*\\.*[:digit:]+"))
# - Next we convert Interaction_Rate to a factor
all_data$Interaction_Rate <- as.factor(all_data$Interaction_Rate)
# - Lastly, we reorder Interaction_Rate based on interval
all_data$Interaction_Rate <- fct_reorder(all_data$Interaction_Rate, all_data$interval)
# Sum numbers in each bin to get correct totals
all_data <- all_data %>% group_by(Interaction_Rate, seed, treatment, update) %>% summarise(count = sum(count)) %>% mutate(rep=seed)## `summarise()` has grouped output by 'Interaction_Rate', 'seed', 'treatment'. You can override using the `.groups` argument.##Data Plots for Host Mean Data
# Make plot
ggplot(all_data %>% filter(treatment==0), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.2), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.3), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.4), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.5), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.6), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.7), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.8), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==0.9), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))
# Make plot
ggplot(all_data %>% filter(treatment==1), aes(x=update,y=count, fill=Interaction_Rate), position='stack') + geom_area() +ylab("Count of Symbionts with Phenotype") + xlab("Evolutionary time (in updates)") +scale_fill_manual("Interaction Rate\n Phenotypes",values=tenhelix) + theme(panel.background = element_rect(fill='light grey', colour='black')) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + guides(fill = "none") + guides(fill = guide_legend())+ facet_wrap(~rep) + theme(axis.text.x = element_text(angle=90, hjust=1))